Overview
- Overview of state-of-the-art methods for model based parameter estimation
- Applications for several scientific disciplines: biology, medicine, chemistry, electrochemistry, environmental physics, image processing and computer vision
- Parameter estimation is a key feature of computational modelling ?
- Includes supplementary material: sn.pub/extras
Part of the book series: Contributions in Mathematical and Computational Sciences (CMCS, volume 4)
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Table of contents (15 chapters)
Keywords
About this book
This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The material chosen was presented at a multidisciplinary workshop on parameter estimation held in 2009 in Heidelberg. The contributions show how indispensable efficient methods of applied mathematics and computer-based modeling can be to enhancing the quality of interdisciplinary research.
The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.
Editors and Affiliations
Bibliographic Information
Book Title: Model Based Parameter Estimation
Book Subtitle: Theory and Applications
Editors: Hans Georg Bock, Thomas Carraro, Willi Jäger, Stefan Körkel, Rolf Rannacher, Johannes P. Schlöder
Series Title: Contributions in Mathematical and Computational Sciences
DOI: https://doi.org/10.1007/978-3-642-30367-8
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-30366-1Published: 05 March 2013
Softcover ISBN: 978-3-642-44076-2Published: 07 March 2015
eBook ISBN: 978-3-642-30367-8Published: 26 February 2013
Series ISSN: 2191-303X
Series E-ISSN: 2191-3048
Edition Number: 1
Number of Pages: X, 334
Number of Illustrations: 57 b/w illustrations, 26 illustrations in colour
Topics: Ordinary Differential Equations, Partial Differential Equations, Numerical Analysis, Computational Science and Engineering, Mathematical Modeling and Industrial Mathematics, Calculus of Variations and Optimal Control; Optimization